Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-23T12:37:20.810Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimating Smooth Country–Year Panels of Public Opinion

Published online by Cambridge University Press:  04 July 2018

Christopher Claassen Open the ORCID record for Christopher Claassen [Opens in a new window]
Christopher Claassen*
Affiliation:
School of Social and Political Sciences, University of Glasgow, Glasgow G12 8QQ, UK. Email: [email protected]
*
*Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

At the microlevel, comparative public opinion data are abundant. But at the macrolevel—the level where many prominent hypotheses in political behavior are believed to operate—data are scarce. In response, this paper develops a Bayesian dynamic latent trait modeling framework for measuring smooth country–year panels of public opinion even when data are fragmented across time, space, and survey item. Six models are derived from this framework, applied to opinion data on support for democracy, and validated using tests of internal, external, construct, and convergent validity. The best model is reasonably accurate, with predicted responses that deviate from the true response proportions in a held-out test dataset by 6 percentage points. In addition, the smoothed country–year estimates of support for democracy have both construct and convergent validity, with spatiotemporal patterns and associations with other covariates that are consistent with previous research.

Keywords

latent variablestime serieshierarchical modelingBayesian estimationpublic opinionsupport for democracy
Type
Articles
Information
Political Analysis , Volume 27 , Issue 1 , January 2019 , pp. 1 - 20
Copyright
Copyright © The Author(s) 2018. Published by Cambridge University Press on behalf of the Society for Political Methodology. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Author’s note: I am grateful for the helpful comments provided by Devin Caughey, Roberto Stefan Foa, Duncan Lee, Anthony J. McGann, Jamie Monogan, and Richard Traunmüller on earlier versions of this paper. I acknowledge the financial support of the Carnegie Trust for the Universities of Scotland and the Adam Smith Research Foundation at the University of Glasgow. Finally, I appreciate the research assistance provided by Jose Ricardo Villanueva Lira and Bryony MacLeod. Replication materials are provided in the Political Analysis dataverse (Claassen 2018).

Contributing Editor: Jonathan N. Katz

References

Almond, Gabriel A., and Verba, Sidney. 1963. The civic culture: Political attitudes and democracy in five nations . Boston: Little & Brown.Google Scholar
Bafumi, Joseph, Gelman, Andrew, Park, David K., and Kaplan, Noah. 2005. Practical issues in implementing and understanding Bayesian ideal point estimation. Political Analysis 13(2):171–187.Google Scholar
Baumgartner, Frank R., De Boef, Suzanna L., and Boydstun, Amber E.. 2008. The decline of the death penalty and the discovery of innocence . New York: Cambridge University Press.Google Scholar
Beck, Nathaniel. 1989. Estimating dynamic models using Kalman filtering. Political Analysis 1:121–156.Google Scholar
Canache, Damarys, Mondak, Jeffery J., and Seligson, Mitchell A.. 2001. Meaning and measurement in cross-national research on satisfaction with democracy. Public Opinion Quarterly 65(4):506–528.Google Scholar
Caughey, Devin, and Warshaw, Christopher. 2015. Dynamic estimation of latent opinion using a hierarchical group-level IRT model. Political Analysis 23(2):197–211.Google Scholar
Carpenter, Bob, Gelman, Andrew, Hoffman, Matthew, Lee, Daniel, Goodrich, Ben, Betancourt, Michael, Brubaker, Marcus, Guo, Jiqiang, Li, Peter, and Riddell, Allen. 2017. Stan: A probabilistic programming language. Journal of Statistical Software 76(1):1–32.Google Scholar
Claassen, Christopher. 2018 Replication data for: Estimating smooth country-year panels of public opinion, https://doi.org/10.7910/DVN/A47LUM, Harvard Dataverse, V3, UNF:6:EbIp/yft64tlqvHHOIx3GA==.Google Scholar
Durbin, James, and Koopman, Siem Jan. 2012. Time series analysis by state space methods . 2nd edn. Oxford: Oxford University Press.Google Scholar
Enns, Peter K. 2016. Incarceration nation: How the United States became the most punitive democracy in the world . New York: Cambridge University Press.Google Scholar
Erikson, Robert S., MacKuen, Michael, and Stimson, James A.. 2002. The macro polity . New York: Cambridge University Press.Google Scholar
Foa, Roberto Stefan, and Mounk, Yascha. 2016. The democratic disconnect. The Journal of Democracy 27(3):5–17.Google Scholar
Fuchs-Schündeln, Nicola, and Schündeln, Matthias. 2015. On the endogeneity of political preferences: Evidence from individual experience with democracy. Science 347(6226):1145–1148.Google Scholar
Gelman, Andrew, and Hill, Jennifer. 2007. Data analysis using regression and multilevel/hierarchical models . New York: Cambridge University Press.Google Scholar
Gibson, James L. 2003. The legacy of apartheid: Racial differences in the legitimacy of democratic institutions and processes in the New South Africa. Comparative Political Studies 36(7):772–800.Google Scholar
Green, Donald P., Gerber, Alan, and De Boef, Suzanna L.. 1999. Tracking opinion over time: A method for reducing sampling error. Public Opinion Quarterly 63:178–192.Google Scholar
Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome. 2009. The elements of statistical learning: Data mining, inference, and prediction . 2nd edn. New York: Springer.Google Scholar
Hjort, Jonas. 2009. Pre-colonial culture, post-colonial economic success? The Tswana and the African Economic Miracle. The Economic History Review 63(3):688–709.Google Scholar
Inglehart, Ronald. 2003. How solid is mass support for democracy – and how can we measure it? PS, Political Science and Politics 36(1):51–57.Google Scholar
Inglehart, Ronald, and Welzel, Christian. 2005. Modernization, cultural change, and democracy: The human development sequence . New York: Cambridge University Press.Google Scholar
Jackman, Simon. 2005. Pooling the polls over an election campaign. Australian Journal of Political Science 40(4):499–517.Google Scholar
Klingemann, Hans-Dieter. 1999. Mapping political support in the 1990s: A global analysis. In Critical citizens: Global support for democratic governance , ed. Norris, Pippa. Oxford: Oxford University Press.Google Scholar
Kurzman, Charles. 2014 World values lost in translation. Washington Post. September 2, online only. https://www.washingtonpost.com/news/monkey-cage/wp/2014/09/02/world-values-lost-in-translation/.Google Scholar
Lewandowski, Daniel, Kurowicka, Dorota, and Joe, Harry. 2009. Generating random correlation matrices based on vines and extended onion method. Journal of Multivariate Analysis 100(9):1989–2001.Google Scholar
Lindberg, Staffan I., Coppedge, Michael, Gerring, John, Teorell, Jan, Pemstein, Daniel, Tzelgov, Eitan, Wang, Yi-ting, Glynn, Adam, Altman, David, Bernhard, Michael, Fish, Steven, Hicken, Alan, Kroenig, Matthew, McMann, Kelly, Paxton, Pamela, Reif, Megan, Skaaning, Svend-Erik, and Staton, Jeffrey. 2014. V-Dem: A new way to measure democracy. Journal of Democracy 25(3):159–169.Google Scholar
Linzer, Drew. 2013. Dynamic Bayesian forecasting of presidential elections in the states. Journal of the American Statistical Association 108(501):124–134.Google Scholar
Lipset, Seymour Martin. 1959. Some social requisites of democracy: Economic development and political legitimacy. American Political Science Review 53(1):69–105.Google Scholar
Mattes, Robert, and Bratton, Michael. 2007. Learning about democracy in Africa: Awareness, performance, and experience. American Journal of Political Science 51(1):192–217.Google Scholar
McGann, Anthony J. 2014. Estimating the political center from aggregate data: An item response theory alternative to the Stimson Dyad ratios algorithm. Political Analysis 22(1):115–129.Google Scholar
McGraw, Kenneth O., and Wong, S. P.. 1996. Forming inferences about some intraclass correlation coefficients. Psychological Methods 1(1):30–46.Google Scholar
Norris, Pippa. 1999. Institutional explanations for political support. In Critical citizens: Global support for democratic governance , ed. Norris, Pippa. Oxford: Oxford University Press.Google Scholar
Park, David K., Gelman, Andrew, and Bafumi, Joseph. 2004. Bayesian multilevel estimation with poststratification: State-level estimates from national polls. Political Analysis 12(4):375–385.Google Scholar
Putnam, Robert D. 1993. Making democracy work: Civic traditions in modern italy . Princeton: Princeton University Press.Google Scholar
Rose, Richard, Mishler, William, and Haerpfer, Christian. 1998. Democracy and its alternatives: Understanding post-communist societies . Baltimore: Johns Hopkins University Press.Google Scholar
Skrondal, Anders, and Rabe-Hesketh, Sophia. Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models . Boca Raton, FL: CRC Press.Google Scholar
Stan Development Team. 2017. Stan modeling language: User’s guide and reference manual: Stan 2.15.0.Stan Development Team.Google Scholar
Stegmueller, Daniel. 2011. Apples and oranges? The problem of equivalence in comparative research. Political Analysis 19(4):471–487.Google Scholar
Stimson, James A. 1991. Public opinion in America: Moods, cycles, and swings, transforming american politics . Boulder, CO: Westview Press.Google Scholar
Stimson, James A., Mackuen, Michael B., and Erikson, Robert S.. 1995. Dynamic representation. American Political Science Review 89(3):543–565.Google Scholar
Sullivan, John L., Piereson, James E., and Marcus, George E.. 1982. Political tolerance and american democracy . Chicago: University of Chicago Press.Google Scholar
Vehtari, Aki, Gelman, Andrew, and Gabry, Johan. 2017. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing 27(5):1413–1432.Google Scholar
Voeten, Erik, and Brewer, Paul R.. 2006. Public opinion, the war in Iraq, and presidential accountability. Journal of Conflict Resolution 50(6):809–830.Google Scholar
Weisberg, Herbert F. 2005. The total survey error approach . Chicago: University of Chicago Press.Google Scholar
Supplementary material: File

Claassen et al. supplementary material

Claassen et al. supplementary material 1

Download Claassen et al. supplementary material(File)
File 3.4 MB